Evaluation of Sunflower (Helianthus annuus L.), Sorghum (Sorghum bicolor L.) and Chinese Cabbage (Brassica chinensis) for Phytoremediation of Lead Contaminated Soils
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The problems associated with heavy metal contamination are widespread and are especially common in developing countries. A pot study was carried out to evaluate the effectiveness of Sunflower (Helianthus annuus), Sorghum (Sorghum bicolor) and Chinese cabbage (Brassica chinensis) at removing lead from the soil. Lead contaminated soils were collected from Kabwe near the old Lead mine and characterized for total and extractable lead, pH, organic matter, texture and cation exchange capacity. The average total and extractable lead concentrations were 23 313 and 5876 mg/kg, respectively, in contaminated soil compared to 57.75 and 10.02 mg/kg in uncontaminated soil. The contaminated soil was then diluted with uncontaminated soil to achieve five contamination levels of 5876, 2500, 1000, 500 and 10.02 mg/kg. Test plants were grown for 10 weeks after which below and above ground dry biomass yields were determined and tested for lead concentration and uptake. Results from this study show that Chinese cabbage is more effective at lead uptake than Sunflower and Sorghum. Results also show that high soil lead concentration results in poor plant growth, low biomass yield and increased lead accumulation in plant tissue.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it